四川地区EC细网格模式2m温度偏差订正研究

本文选取2017年1~12月ECMWF(European Centre for Medium-Range Weather Forecasting)细网格模式168h预报时效的2m温度场和对应时段四川地区157个国家站的观测资料,对比分析了模式温度预报的系统性偏差特征,采用15日周期的滑动双权重平均法对2m温度预报产品进行偏差订正,并与四川省气象台现有的主、客观预报产品进行对比,结果表明:(1)EC模式对低温的预报准确率远高于高温预报准确率;订正后高、低温预报准确率均有显著提高,其中低温平均提高了20.5%,高温提高了31.2%,平均绝对误差分别减小约1.1℃和2.9℃。(2)EC模式高温预报的逐月差异明显比低温预报逐月差异大,订正后差异明显减小,且各月的高、低温预报准确率均有显著提升,订正后各月高、低温的平均绝对误差均在2℃之内。(3)EC模式对于低温和高温的预报在全省均大致呈现负的系统性误差,且高温预报的系统性误差明显比低温预报的系统性误差大,订正后2m温度预报的系统性误差均明显降低,全省大部分地区维持在±1℃之间。(4)与四川省气象台现有的主、客观预报产品对比显示,对于高低温预报均是EC订正后准确率最高、平均绝对误差最小,订正效果较为理想。     

气象站迁站前后气温同期观测资料对比

通过对山东省东阿县新旧地面气象观测站同期(2008年1、4、7月)气温观测资料对比分析,发现两站之间气温存在明显的正温差,旧测站气温存在城市热岛效应。这种效应夜间大于白天,冬、春(秋)季较为明显,夏季最小;城市热岛效应使最低气温下降,从而减小气温日较差,故旧测站气温较高;统计检验表明,旧测站与新测站气温存在显著的正相关,但两地气温差异显著,两地气温资料已经不适合合并计算。所以,对于旧测站的气温记录,应做出必要的订正后,才能得到较准确的代表当地气温的统计资料。     

微波湿度计资料在GRAPES模式中偏差订正方法研究

根据微波湿度计MHS(Microwave Humidity Sounder)辐射率资料及GRAPES(Global/Regional Assimilation and Pr Ediction System)模式的特点,建立适用于MHS资料的偏差订正系统,该系统包括扫描和气团偏差订正,其中气团偏差订正考虑水汽资料的特性,采用三种不同预报因子组合的方案。偏差订正结果表明:MHS各个通道的扫描偏差表现出不同特征;偏差订正后观测残差基本服从均值为零的高斯分布,且观测残差的均值有所降低并随时间变化平稳;三种气团偏差订正方案都有明显的订正效果,其中方案三的订正效果最佳。     

FY-3A微波资料偏差订正及台风路径预报应用

我国极轨气象卫星FY-3A大大增强了对地球系统的综合探测能力,而偏差订正对卫星资料的应用非常必要。试验中FY-3A卫星微波资料的偏差订正方案是在Harris等的TOVS辐射资料偏差订正经验方法的基础上结合WRF-3DVAR系统发展的,偏差订正后微波资料各通道拟合结果基本位于主对角线上,大多数卫星观测数据与观测算子利用背景场计算的亮温值分布趋于合理,偏差得到很大程度的降低。偏差订正后,利用数值模式直接同化FY-3A气象卫星微波资料,通过对2008年和2009年的4个台风进行预报评估表明:同化FY-3A气象卫星资料后路径预报能力提高明显,尤其是36 h后路径预报结果;同化FY-3A气象卫星微波资料后台风预报路径误差平均降低20%,而只同化常规资料路径误差仅仅降低了4%。     

ECWMF高分辨率模式2m温度预报在六盘水市的误差分析及订正指标

采用气候概率统计和多时效平均的思路,对2018—2019年的欧洲中期天气预报中心（ECWMF）高分辨率模式2 m温度产品在六盘水市的预报误差进行统计分析,并对采用指标订正后的2020年度模式预报准确率进行检验评估。结果表明：ECWMF高分辨率模式对六盘水市的温度预报误差随时效的增加而逐渐减小,且各时效平均的最高温度年均预报误差和误差标准差要明显高于最低温度;对于六盘水而言,模式的温度预报在初夏（6月）可靠性最高,而在春季（3—4月）最低;通过采用预报误差最大占比对逐月多时效平均的模式最低温度预报进行订正,以及根据天气类型采用不用订正方式与订正指标对模式24 h最高温度预报进行订正,能够大幅提升全市未来5 d（120 h）综合最低温度和24 h内的最高温度预报准确率,分别稳定在90%和70%以上;经过订正后,全市的2020年度平均最低温度预报准确率与实际相当,而24 h最高温度预报准确率要高于实际预报准确率。     

基于短期历史资料的河西地区太阳辐射预报订正研究

基于数值模式的太阳辐射预报往往存在一定的系统性偏差,AVT订正方法能够有效降低预报偏差,本文利用该方法对甘肃河西地区两个光伏电站的太阳辐射预报结果进行订正。结果表明：(1)订正前预报偏差呈现明显的“先增加、后减小”日变化特征,订正后日变化特征不明显,并且订正前预报偏差与观测值线性关系显著,订正后线性关系减弱(相关系数降低、拟合优度降低);(2)太阳辐射存在明显的年变化特征,其预报偏差春季最高,其次为夏季,冬季最小,订正后不同季节的预报偏差均降低,春季和夏季降低较为明显。     

The Characteristics of Cold Air Outbreaks over the Eastern Highlands of Kenya

Summary Climatological statistics of extreme temperature events over Kenya are established from the analysis of daily and monthly maximum temperatures for a representative station (Nairobi Dagoretti Corner) over the period 1956–1997. The months of June to August were shown to be the coldest with a mean monthly maximum temperature of less than 22 °C. Seasonal (June to August) mean maximum temperature was 21.5 °C. Using this seasonal mean temperature for the period 1967–1997 delineated 1968 as the coldest year in this series and 1983 as the warmest year. Spectral analysis of the seasonal data, for both the coldest and the warmest years, revealed that the major periods were the quasi-biweekly (10 days) and the Intraseasonal Oscillations (23 days). Secondary peaks occurred at periods of 4–6 and 2.5–3.5 days. A temperature threshold of 16.7 °C during July was used to define cold air outbreaks over Nairobi. This threshold temperature of 16.7 °C was obtained from the mean July maximum temperature (20.9 °C) minus two standard deviations. Notable trends include a decrease in the frequency of station-days, between 1956 and 1997, with temperatures less than 16.7 °C during July. Surface pressure patterns indicate that the origin of the cold air is near latitude 25° S and to the east of mainland South Africa. The cold air near 25° S is advected northwards ahead of the surface pressure ridge. Received July 19, 1999 Revised January 11, 2000     

南京地区人体舒适度及其与居民循环系统疾病死亡关系的研究

选取南京地区1961年1月1日至2012年12月31日逐日地面气象观测资料,采用“黄金分割法”计算体感温度,分析南京地区近52年舒适度特征;选取2005年1月1日至2008年12月31日逐日循环系统疾病死亡人数资料和同期气象资料,分析南京市2005-2008年舒适度和体感温度特征及其与循环系统疾病死亡人数的关系。结果表明,1961-2012年南京市热不舒适期、舒适期日数呈现上升趋势,而冷不舒适期日数呈显著减少趋势,变化率为－3.2 d/10a;4月上旬至5月中旬和10月为舒适期;体感温度在20世纪中期之后表现为明显的上升趋势,增加率为0.3℃/10a;2005-2008年舒适度以微冷和舒适为主;死亡高峰日多出现在冷不舒适日,2008年初死亡高峰日持续时间较长,且与天气灾害过程发生时间存在7～9 d的滞后。     

基于卡尔曼滤波递减平均算法的集合预报综合偏差订正

针对集合预报存在的偏差和集合离散度通常偏小的问题,在卡尔曼滤波递减平均的一阶矩和二阶矩偏差订正方案的基础上发展了综合偏差订正方案,并利用B08RDP WWRP(The WWRP Beijing 2008 Olympics Research and Development Project)项目中日本气象厅(JMA)区域集合预报的850 hPa温度资料,将敏感性试验得到的一阶矩和二阶矩订正的最优权重系数应用于综合偏差订正方案,并对其订正效果进行多方面检验分析。试验结果表明,一阶矩订正可以有效减小集合平均偏差,集合平均预报质量得到了明显改善;二阶矩订正对集合离散度具有较强的调整能力,订正后的集合预报可靠性、区分不同天气事件的能力总体上得到了提高;综合偏差订正方案有效融合了一阶矩和二阶矩订正的优势,其各自的最优权重系数适用于综合偏差订正方案,对集合平均偏差和离散度具有良好的订正效果,能够改善集合预报的整体质量。但一阶矩与二阶矩订正对综合偏差订正的贡献程度随评分指标而异,一阶矩订正对等级概率(RPS)评分和异常值百分比评分的贡献分别为83.75%和18.83%,可信度的改善约83.98%源于二阶矩订正,而相对作用特征(ROC)评分中二者的贡献基本相当。     

Sensitivity of ENSO characteristics to a new interactive flux correction scheme in a coupled GCM

A fast coupled global climate model (CGCM) is used to study the sensitivity of El Ni?o Southern Oscillation (ENSO) characteristics to a new interactive flux correction scheme. With no flux correction applied our CGCM reveals typical bias in the background state: for instance, the cold tongue in the tropical east Pacific becomes too cold, thus degrading atmospheric sensitivity to variations of sea surface temperature (SST). Sufficient atmospheric sensitivity is essential to ENSO. Our adjustment scheme aims to sustain atmospheric sensitivity by counteracting the SST drift in the model. With reduced bias in the forcing of the atmosphere, the CGCM displays ENSO-type variability that otherwise is absent. The adjustment approach employs a one-way anomaly coupling from the ocean to the atmosphere: heat fluxes seen by the ocean are based on full SST, while heat fluxes seen by the atmosphere are based on anomalies of SST. The latter requires knowledge of the model??s climatological SST field, which is accumulated interactively in the spin-up phase (??training??). Applying the flux correction already during the training period (by utilizing the evolving SST climatology) is necessary for efficiently reducing the bias. The combination of corrected fluxes seen by the atmosphere and uncorrected fluxes seen by the ocean implies a restoring mechanism that counteracts the bias and allows for long stable integrations in our CGCM. A suite of sensitivity runs with varying training periods is utilized to study the effect of different levels of bias in the background state on important ENSO properties. Increased duration of training amplifies the coupled sensitivity in our model and leads to stronger amplitudes and longer periods of the Nino3.4 index, increased emphasis of warm events that is reflected in enhanced skewness, and more pronounced teleconnections in the Pacific. Furthermore, with longer training durations we observe a mode switch of ENSO in our model that closely resembles the observed mode switch related to the mid-1970s ??climate shift??.     

浅析啤酒销售与气象要素的关系及预测

利用1997年1月-2002年6月兰州市某大型啤酒企业啤酒销售资料与同期兰州市气象要素资料，分析气象要素对啤酒销售的影响。分析结果表明，温度是影响啤酒销售量最显著的气象因子。两者具有很好的相关性。采用最小二乘法建立啤酒销售量的月及逐日预报方程。并提出啤酒指数的概念。     

Estimation and correction of model bias in the NASA/GMAO GEOS5 data assimilation system: Sequential implementation

This study presents a simplified multivariate bias correction scheme that is sequentially implemented in the GEOS5 data assimilation system and compared against a control experiment without model bias correction. The results show considerable improvement in terms of the mean biases of rawinsonde observation-minus-background (OmB) residuals for observed water vapor, wind and temperature variables. The time series spectral analysis shows whitening of bias-corrected OmB residuals, and mean biases for rawinsonde observation-minus-analysis (OmA) are also improved. Some wind and temperature biases in the control experiment near the equatorial tropopause nearly vanish from the bias-corrected experiment. Despite the analysis improvement, the bias correction scheme has only a moderate impact on forecast skill. Significant interaction is also found among quality-control, satellite observation bias correction, and background bias correction, and the latter positively impacts satellite bias correction.     

Peninsular Indian rainfall and its association with meteorological and oceanic parameters over the Indian Ocean

The present study attempts to formulate a regression model to predict summer rainfall over Peninsular India (PIR) using some regional predictors. Parameters having significant correlation (99%) with PIR were identified for the period 1975–1997 (training), and a 15-year sliding correlation (90%) was found to check the consistency of the relationship between PIR and predictors. From a set of 14 candidate predictors, 4 were selected using a stepwise regression method and tested over a period from 1998 to 2006. The predictors selected are sea surface temperature during March over Indian Ocean, air temperature at 850?hPa during May over Peninsular India, zonal, and meridional wind at 700?hPa during February and January, respectively, over the Arabian Sea. The model captures a variance of 77.7% and has a multiple correlation of 0.88. The root mean square error, absolute mean error, and bias for the training (test) period were 7.6% (21.5%), 6.6% (17.9%), and 0% (11.4%) of mean rainfall, respectively. Results of the climatological predictions show that the model developed is useful.     

Arctic warming,moisture increase and circulation changes observed in the Ny-Ålesund homogenized radiosonde record

The interannual variability of precipitation and temperature is derived from all runs of the Intergovernmental Panel on Climate Change (IPCC) fourth Assessment Report (AR4)-based two Atmospheric Oceanic General Circulation Model (AOGCM) simulations, over Pakistan, on an annual basis. The models are the CM2.0 and CM2.1 versions of Geophysical Fluid Dynamics Laboratory (GFDL)-based AOGCM. Simulations for a recent 22-year period (1979–2000) are validated using Climate Research Unit (CRU) and NCEP/NCAR datasets over Pakistan, for the first time. The study area of Pakistan is divided into three regions: all Pakistan, northern Pakistan, and southern Pakistan. Bias, root mean square error, one sigma standard deviation, and coefficient of variance are used as validation metrics. For all Pakistan and northern Pakistan, all three runs of GFDL-CM2.0 perform better under the above metrics, both for precipitation and temperature (except for one sigma standard deviation and coefficient of variance), whereas for southern Pakistan, third run of GFDL-CM2.1 perform better expect for the root mean square error for temperature. A mean and variance-based bias correction is applied to bias in modeled precipitation and temperature variables. This resulted in a reduced bias, except for the months of June, July, and August, when the reduction in bias is relatively lower.     

Analysis of Atmospheric Boundary Layer Height Characteristics over the Arctic Ocean Using the Aircraft and GPS Soundings

Utilizing aircraft sounding data collected from the Surface Heat Budget of the Arctic Ocean (SHEBA, 1998) campaign, the authors evaluated commonly-used profile methods for Arctic ABL height estimation by validating against the’true’ABL height from aircraft sounding profiles, where ABL height is defined as the top of the layer with significant turbulence. Furthermore, the best performing method was used to estimate ABL height from the one-year GPS soundings obtained during SHEBA (October 1997-October 1998). It was found that the temperature gradient method produces a reliable estimate of ABL height. Additionally, the authors determined optimal threshold values of temperature gradient for stable boundary layer (SBL) and convective boundary layer (CBL) to be 6.5 K/100 m and 1.0 K/100 m, respectively. The maximum ABL height during the year was 1150 m occurred in May. Median values of Arctic ABL height in May, June, July, and August were 400 m, 430 m, 180 m, and 320 m, respectively. Arctic ABL heights are clearly higher in the spring than in the summer.     

不同分辨率再分析资料对浙江省气温刻画能力的对比评估

利用浙江省66个基本气象站1979—2010年的日平均气温数据,系统评估了三套再分析资料R1、R2和CFSR对浙江省气温的刻画能力。结果表明:三套再分析资料的气候平均态与观测均存在一定差异,其中R1、R2的空间分布型与观测较为接近,CFSR与观测差异较大;三套再分析资料均存在系统性冷偏差且这一偏差在32年中稳定存在,其中CFSR的冷偏差更显著,浙南地区是其冷偏差的重要来源。三套资料的均方根误差均存在季节变化:冬季（特别是1月）误差较小而夏季（特别是7-8月）误差较大,R1和R2的季节差异强于CFSR。CFSR对浙江省气温变率的把握能力优于R1和R2,其距平场EOF分解前三模态的空间型态和时间系数与观测更为接近。系统误差订正后,三套再分析资料的可信度得到显著改善,CFSR的改善效果最明显,说明系统性误差是三套再分析资料偏差的重要来源。改善后三套再分析资料的均方根误差和空间相关系数大体相当。CFSR网格点气温插值到观测站点时因海拔差异导致的误差以及CFSR在浙江省的模式地形偏高可能是其有较大冷偏差的重要原因。      

On the use of radiosonde humidity observations in mid-latitude NWP

Summary We compare radiosonde observations of relative humidity with NWP versions of the Meteorological Office Unified Model, and attempt to understand the causes of the systematic differences seen. The differences are found to have a different structure in cyclonic and anticyclonic situations over the UK. In cyclonic situations the mid-tropospheric temperature and humidity differences could be due to model biases, consistent with the conservation of energy; the latent heating from precipitation of the model's excess moisture would remove the model's cold bias. There is also some evidence for observational bias. Wetting of the sonde sensor in cloud can cause a moist bias at higher levels. The Väisala RS80 sonde also appears to have a dry bias near saturation.The Unified Model has a parameterisation for stratiform cloud which calculates the fractional cloud cover in a gridbox from the box-average relative humidity, allowing for sub-grid-scale variability within the box. This scheme has been tuned to give reasonable cloud amounts with the model's relative humidities. The cloud amounts implied (by the scheme) for radiosonde relative humidities are systematically less than the observed cloud. So assimilation of the observed humidities can significantly degrade analyses and predictions of cloud. Bias corrections for the radiosonde humidities have been calculated to compensate for this.Experiments have been performed to test the effect of the bias correction on the assimilation and prediction of cloud and precipation. With the control system, cloud cover and precipitation spins-up during the forecast period; the bias correction improves this. A large improvement was also found when the relationship between the temperature and humidity assimilation was changed; it is better to assume that temperature and relative humidity errors are uncorrelated, rather than temperature and specific humidity.With 16 Figures     

NEX-GDDP和CMIP5对青藏高原地区近地面气象场历史和未来模拟的评估与偏差校正

青藏高原是全球变化研究的热点区域,气候模式模拟是研究该区域气候变化的重要数据来源.本文使用基于中国地面台站的插值格点数据集(CN05.1),对国际气候耦合模式第5次比较计划(CMIP5)及其高分辨率统计降尺度数据集(NEX-GDDP)中15个模式1966-2005年间的逐日最高/最低气温、降水和平均风速在青藏高原区域的...     

风电场风速数值预报的误差分析及订正

使用WRF模式对内蒙古某风电场区域内的2011年1-6月,50m高度的风速进行了模拟,并结合实测风速对模拟结果进行了评估。在此基础上再利用自回归模型(AR模型)和持续法对WRF模式模拟结果进行了订正预报,订正结果表明:AR模型和持续法都能有效地减小WRF模式风速的模拟误差,AR模型订正效果优于持续法。为能对订正预报时效进行延长,提出了"假设观测值"概念。在AR模型的基础上建立一种新的订正模型称之为New AR模型。其订正预报结果表明:新模型能在12h时效内,改善WRF模式风速模拟精度,其中6h的改进效果较好。     

BCC_CSM1.1m模式对福建前汛期降水预测的误差订正

采用1991—2017年BCC_CSM1.1m季节预测模式的月降水预测数据及福建省前汛期（4—6月）66个国家气象站降水资料,利用距平相关系数(ACC)、时间相关系数(TCC)、平均方差技巧评分(MSSS)和趋势异常综合评分(Ps)等评估方法,检验评估了提前0、1、2和5个月模式对福建省前汛期降水的预测能力。采用系统偏差、一元线性回归和EOF-相似误差（EOFL和EOFNL）等4种统计方法对回报结果进行订正,并进行效果检验。BCC_CSM1.1m在不同起报时间对福建省前汛期降水的预测均能抓住降水的前两个主模态：全省一致和南北反向分布的空间特征,但预测的气候平均值较实况存在负偏差。模式在不同起报时间对前汛期降水预测的TCC高技巧区主要位于福建省北部,ACC技巧和Ps评分存在比较大的年际差异,负系统偏差的存在使得MSSS技巧不高。经订正后,模式的预测能力得到明显提升。系统偏差、线性回归、EOF相似误差线性和非线性订正方法提前2个月起报的2011—2017年平均Ps评分分别提高5.9、3.5、6.7和7.8分;不同起报时间线性回归订正的2011—2017年平均ACC技巧分别提高0.02、0.21、0.12和0.11;上述4种方法订正的MSSS评分均有了显著提高,其中系统偏差和线性回归订正后达正技巧。综合而言,线性回归订正较其他3种订正方法表现出更为稳定的订正技巧。